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danielklecha

mcp-server-for-powershell

by danielklecha
OverviewSchemaRelated ServersScoreDiscussions
Python

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.4

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap. The agent can uniquely identify the tool's purpose without ambiguity.

    Naming Consistency5/5

    The single tool name follows a clear verb_noun pattern (run_powershell), which is consistent and readable. Since there's only one tool, no convention conflicts exist.

    Tool Count3/5

    The server has only one tool for the broad domain of PowerShell execution. While the tool is versatile, it forces the agent to encode all operations as complex JSON, which is less ergonomic than dedicated tools for common tasks. The count is borderline.

    Completeness4/5

    The single tool can theoretically execute any PowerShell command, covering the domain of command execution comprehensively. However, it lacks specialized tools for session management, script handling, or error recovery, which may be needed for complex workflows.

  • Average 3.9/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description must disclose behavioral traits alone. It only mentions 'Executes PowerShell commands... safely strings' (vague) and returns standard output or error. It does not disclose security implications, required permissions, sandboxing, or limitations on commands. This is insufficient for a command execution tool that could be destructive.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is relatively long due to detailed examples, which are justified given the complexity of the input format. It is well-structured with bullet points and clear sections (Args, Returns). The main purpose is front-loaded. Could be slightly trimmed, but overall efficient for the required detail.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's potential to execute arbitrary code and the presence of an output schema (not shown), the description is moderately complete. It covers input format well but lacks details on execution environment, error handling, performance considerations, or return value structure beyond 'standard output'. This leaves gaps for an agent deciding to use the tool.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema has 0% description coverage for the single parameter 'json', but the description compensates richly with seven examples of valid JSON structures, covering single commands, pipelines, and sequences. This adds significant meaning beyond the schema's raw 'string' type, making it very helpful for the agent.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Executes PowerShell commands based on a structured JSON definition.' The verb 'executes' and the resource 'PowerShell commands' are specific, and the JSON-based input distinguishes it from general command execution. Despite an awkward phrase ('safely strings'), the purpose is unambiguous.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    While there are no sibling tools, the description provides extensive guidance on how to format the input, including multiple examples of single commands, .NET methods, named parameters, pipelines, and sequences. However, it does not explicitly state when to use this tool or mention any prerequisites (e.g., PowerShell availability). The implied context is sufficient for an AI agent to understand usage.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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